Search Results (3,596)

Due to global warming, extreme temperature events have become increasingly prevalent, posing significant threats to both socioeconomic development and human safety. While previous studies have extensively examined the influence of individual climatic circulation systems on extreme temperature, the combined effects of multiple concurrent circulation patterns remain poorly understood. Using daily temperature data from 29 meteorological stations in Chongqing (1960–2019), this study employs linear trend analysis, correlation analysis, and random forest (RF) models to analyze spatiotemporal variations in the intensity and frequency of extreme temperature. We selected 21 climate indicators from three categories—atmospheric circulation, sea surface temperature (SST), and sea-level pressure (SLP)—to identify the primary drivers of extreme temperatures and quantify their respective contributions. The key findings are as follows: (1) All extreme intensity indices exhibited an increasing trend, with the TXx (annual maximum daily maximum temperature) showing the higher trend (0.03 °C/year). The northeastern region experienced the most pronounced increases. (2) Frequency indices also displayed an upward trend. This was particularly evident for the TD35 (number of days with maximum temperature ≥35 °C), which increased at an average rate of 0.16 days/year, most notably in the northeast. (3) The Western Pacific Subtropical High Ridge Position Index (GX) and Asia Polar Vortex Area Index (APV) were the dominant climate factors driving intensity indices, with cumulative contributions of 26.0% to 33.4%, while the Western Pacific Warm Pool Strength Index (WPWPS), Asia Polar Vortex Area Index (APV), North Atlantic Subtropical High Intensity Index (NASH), and Indian Ocean Warm Pool Strength Index (IOWP) were the dominant climate factors influencing frequency indices, with cumulative contributions of 46.4 to 49.5%. The explanatory power of these indices varies spatially across stations, and the RF model effectively identifies key circulation factors at each station. In the future, more attention should be paid to urban planning adaptations, particularly green infrastructure and land use optimization, along with targeted heat mitigation strategies, such as early warning systems and public health interventions, to strengthen urban resilience against escalating extreme temperatures. Full article

As key components of the climate system, clouds exert a significant influence on the Earth’s radiation budget and hydrological cycle. However, studies focusing on cloud properties over Central Asia are still limited, and the impacts of cloud variability on regional temperature and precipitation remain poorly understood. This study uses reanalysis and multi-source remote sensing datasets to investigate the spatiotemporal characteristics of clouds and their influence on regional climate. The cloud cover increases from the southwest to the northeast, with mid and low-level clouds predominating in high-altitude regions. All clouds have shown a declining trend during 1981–2020. According to satellite data, the sharpest decline in total cloud cover occurs in summer, while reanalysis data show a more significant reduction in spring. In addition, cloud cover changes influence the local climate through radiative forcing mechanisms. Specifically, the weakening of shortwave reflective cooling and the enhancement of longwave heating of clouds collectively exacerbate surface warming. Meanwhile, precipitation is positively correlated with cloud cover, and its spatial distribution aligns with the cloud water path. The cloud phase composition in Central Asia is dominated by liquid water, accounting for over 40%, a microphysical characteristic that further impacts the regional hydrological cycle. Full article

Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article

The coastal sandy land in northeast Hainan Province is typical for this land type, also exhibiting strong sand activity. This study is based on wind speed, wind direction, and sediment transport data obtained at a field meteorological station using an omnidirectional sand accumulation instrument from 2020 to 2024, studying the coastal aeolian environment and sediment transport distribution characteristics in the region. Its findings provide a theoretical basis for comprehensively analyzing the evolution of coastal aeolian landforms and the evaluation and control of coastal aeolian hazards. The research results show the following: (1) The annual average threshold wind velocity for sand movement in the study area is 6.84 m/s, and the wind speed frequency (frequency of occurrence) is 51.54%, dominated by easterly (NE, ENE) and southerly (S, SSE) winds. (2) The drift potential (DP) refers to the potential amount of sediment transported within a certain time and spatial range, and the annual drift potential (DP) and resultant drift potential (RDP) of Mulan Bay from 2020 to 2024 were 550.82 VU and 326.88 VU, respectively, indicating a high-energy wind environment. The yearly directional wind variability index (RDP/DP) was 0.59, classified as a medium ratio and indicating blunt bimodal wind conditions. The yearly resultant drift direction (RDD) was 249.45°, corresponding to a WSW direction, indicating that the sand in Mulan Bay is generally transported in the southwest direction. (3) When the measured data extracted from the sand accumulation instrument in the study area from 2020 to 2024 were used for statistical analysis, the results showed that the total sediment transport rate (the annual sediment transport of the observation section) in the study area was 110.87 kg/m·a, with the maximum sediment transport rate in the NE direction being 29.26 kg/m·a. These results suggest that when sand fixation systems are constructed for relevant infrastructure in the region, the construction direction of protective forests and other engineering measures should be perpendicular to the net direction of sand transport. Full article

This study analyzes spatiotemporal aridity dynamics in Central Kazakhstan (1960–2022) using a monthly Aridity Index (AI = P/PET), where P is precipitation and PET is potential evapotranspiration, Mann–Kendall trend analysis, and climate zone classification. Results reveal a northeast–southwest aridity gradient, with Aridity Index ranging from 0.11 to 0.14 in southern deserts to 0.43 in the Kazakh Uplands. Between 1960–1990 and 1991–2022, southern regions experienced intensified aridity, with Aridity Index declining from 0.12–0.15 to 0.10–0.14, while northern mountainous areas became more humid, where Aridity Index increased from 0.40–0.44 to 0.41–0.46. Seasonal analysis reveals divergent patterns, with winter showing improved moisture conditions (52.4% reduction in arid lands), contrasting sharply with aridification in spring and summer. Summer emerges as the most extreme season, with hyper-arid zones (8%) along with expanding arid territories (69%), while autumn shows intermediate conditions with notable dry sub-humid areas (5%) in northwestern regions. Statistical analysis confirms these observations, with northern areas showing positive Aridity Index trends (+0.007/10 years) against southwestern declines (−0.003/10 years). Key drivers include rising temperatures (with recent degradation) and variable precipitation (long-term drying followed by winter and spring), and PET fluctuations linked to temperature. Since 1991, arid zones have expanded from 40% to 47% of the region, with semi-arid lands transitioning to arid, with a northward shift of the boundary. These changes are strongly seasonal, highlighting the vulnerability of Central Kazakhstan to climate-driven aridification. Full article

An in-depth understanding of the spatiotemporal heterogeneity of ecosystem service (ES) trade-offs and synergies, along with their driving factors, is crucial for formulating key ecological restoration strategies and effectively allocating ecological environmental resources in the Hulunbuir region. This study employed an integrated analytical approach combining the InVEST model, ArcGIS geospatial processing, R software environment, and Optimal Parameter Geographical Detector (OPGD). The spatiotemporal patterns and driving factors of the interaction of four major ES functions in Hulunbuir area from 2000 to 2020 were studied. The research findings are as follows: (1) carbon storage (CS) and soil conservation (SC) services in the Hulunbuir region mainly show a distribution pattern of high values in the central and northeast areas, with low values in the west and southeast. Water yield (WY) exhibits a distribution pattern characterized by high values in the central–western transition zone and southeast and low values in the west. For forage supply (FS), the overall pattern is higher in the west and lower in the east. (2) The trade-off relationships between CS and WY, CS and SC, and SC and WY are primarily concentrated in the western part of Hulunbuir, while the synergistic relationships are mainly observed in the central and eastern regions. In contrast, the trade-off relationships between CS and FS, as well as FS and WY, are predominantly located in the central and eastern parts of Hulunbuir, with the intensity of these trade-offs steadily increasing. The trade-off relationship between SC and FS is almost widespread throughout HulunBuir. (3) Fractional vegetation cover, mean annual precipitation, and land use type were the primary drivers affecting ESs. Among these factors, fractional vegetation cover demonstrates the highest explanatory power, with a q-value between 0.6 and 0.9. The slope and population density exhibit relatively weak explanatory power, with q-values ranging from 0.001 to 0.2. (4) The interactions between factors have a greater impact on the inter-relationships of ESs in the Hulunbuir region than individual factors alone. The research findings have facilitated the optimization and sustainable development of regional ES, providing a foundation for ecological conservation and restoration in Hulunbuir. Full article

Glanders is a highly contagious and often fatal zoonotic disease of equids caused by Burkholderia mallei, a pathogen of significant concern due to its potential for bioterrorism. In Brazil, glanders remains endemic, particularly among working equids in the Northeast region. Diagnostic confirmation typically involves serology, culture, and polymerase chain reaction (PCR), although false-negative PCR results have been increasingly reported. This study aimed to evaluate the diagnostic performance and analytical sensitivity of four B. mallei-specific PCR primer sets using samples from 30 seropositive equids. Microbiological cultures were obtained from various organs and swabs, followed by PCR targeting four genomic regions: fliP-IS407A(a), fliP-IS407A(b), Burk457, and Bm17. All animals were confirmed positive for B. mallei via culture, but PCR detection rates varied significantly across primer sets. The fliP-IS407A(b) primer set showed the highest sensitivity, detecting 86% of samples, while the WOAH-recommended fliP-IS407A(a) set had the lowest performance (13.4%). Analytical sensitivity assays confirmed that fliP-IS407A(b) and Bm17 primers detected DNA concentrations as low as 0.007 ng, outperforming the others. These findings suggest that certain widely used primer sets may lack sufficient sensitivity for reliable detection of B. mallei, especially in chronically infected animals with low bacterial loads. The study underscores the need for ongoing validation of molecular diagnostics to improve the detection and control of glanders in endemic regions. Full article

True slime molds (Eumycetozoa) remain under-explored globally, particularly in water-logged forest habitats. Despite evidence suggesting a high biodiversity potential in the Knyszyn Forest of north-eastern Poland, no systematic effort had previously been undertaken there. In the present survey, plant substrates from eight swampy sub-compartments were incubated for over four months, resulting in the detection of fifteen slime mold species. Four of these taxa are newly reported for northern and north-eastern Poland, while several have been recorded only a handful of times in the global literature. These findings underscore how damp, nutrient-rich conditions foster Eumycetozoa and demonstrate the effectiveness of moist-chamber culturing in revealing rare or overlooked taxa. Current evidence shows that, although slime molds may occasionally colonize living plant or fungal tissues, their influence on crop productivity and tree vitality is negligible; they are therefore better regarded as biodiversity indicators than as pathogens or pests. By establishing a replicable framework for studying water-logged environments worldwide, this work highlights the ecological importance of swamp forests in sustaining microbial and slime mold diversity. Full article

Understanding the impacts of climate change on species’ geographic distributions is fundamental for biodiversity conservation and resource management. As a key plant group for ecological restoration and windbreak and sand fixation in arid and semi-arid ares in China’s Three Northern Regions (Northeast, North, and Northwest China), Caragana spp. exhibit distribution patterns whose regulatory mechanisms by environmental factors remain unclear, with a long-term lack of climatic explanations influencing their spatial distribution. This study integrated 2373 occurrence records of 44 Caragana species in China’s Three Northern Regions with four major environmental variable categories. Using the Biomod2 ensemble model, current and future climate scenario-based suitable habitats for Caragana spp. were predicted. This study innovatively combined quantitative analyses with Kira’s thermal indexes (warmth index, coldness index) and Wenduo Xu’s humidity index (HI) to elucidate species-specific relationships between distribution patterns and hydrothermal climatic constraints. The main results showed that (1) compared to other environmental factors, climate is the key factor affecting the distribution of Caragana spp. (2) The current distribution centroid of Caragana spp. is located in Alxa Left Banner, Inner Mongolia. In future scenarios, the majority of centroids will shift toward lower latitudes. (3) The suitable habitats for Caragana spp. will expand overall under future climate scenarios. High-stress scenarios exhibit greater spatial changes than low-stress scenarios. (4) Hydrothermal requirements varied significantly among species in China’s Three Northern Regions, and 44 Caragana species can be classified into five distinct types based on warmth index (WI) and humidity index (HI). The research findings will provide critical practical guidance for ecological initiatives such as the Three-North Shelterbelt Program and the restoration and management of degraded ecosystems in arid and semi-arid regions under global climate change. Full article

As a cultural corridor connecting the Central Plains and Northeast China, the Liaoxi Corridor has a special position in the transmission of traditional Chinese culture. Traditional villages in the region have preserved rich intangible cultural heritage and traditional architectural features, which highlight the historical heritage of multicultural intermingling. This study fills the gap in the spatial distribution of traditional villages in the Liaoxi Corridor and reveals their spatial distribution pattern, which is of great theoretical significance. Using Geographic Information System (GIS) spatial analysis and quantitative geography, this study analyzes the spatial pattern of traditional villages and the influencing factors. The results show that traditional villages in the Liaoxi Corridor are clustered, forming high-density settlement areas in Chaoyang County and Beizhen City. Most villages are located in hilly and mountainous areas and river valleys and are affected by the natural geographic environment (topography and water sources) and historical and human factors (immigration and settlement, border defense, ethnic integration, etc.). In conclusion, this study provides a scientific basis and practical reference for rural revitalization, cultural heritage protection, and regional coordinated development, aiming at revealing the geographical and cultural mechanisms behind the spatial distribution of traditional villages. Full article

The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination of paired t-test, geostatistics, correlation analysis, and principal component analysis to systematically reveal the spatial differentiation of soil nutrients in the black soil layer and white clay layer of dryland albic soil, and to clarify the impact mechanism of plow layer nutrient characteristics on crop productivity. The results show that the nutrient content order in both the black and white clay layers is consistent: total potassium (TK) > organic matter (OM) > total nitrogen (TN) > total phosphorus (TP) > alkali-hydrolyzable nitrogen (HN) > available potassium (AK) > available phosphorus (AP). Both layers exhibit a spatial pattern of overall consistency and local differentiation, with spatial heterogeneity dominated by altitude gradients—nutrient content increases with decreasing altitude. Significant differences exist in nutrient content and distribution between the black and white clay layers, with the comprehensive fertility of the black layer being significantly higher than that of the white clay layer, particularly for TN, TP, TK, HN, and OM contents (effect size > 8). NDVI during the full maize growth period is significantly positively correlated with TP, TN, AK, AP, and HN, and the NDVI dynamics (first increasing. then decreasing) closely align with the peak periods of available nitrogen/phosphorus and crop growth cycles, indicating a strong coupling relationship between vegetation biomass accumulation and nutrient availability. These findings provide important references for guiding rational fertilization, agricultural production layout, and ecological environmental protection, contributing to the sustainable utilization of dryland albic soil resources and sustainable agricultural development. Full article

The 13th International Foamy Virus (FV) Conference was held from 8 to 10 November 2023 at the BioParque/Zoological Garden in Rio de Janeiro, Brazil. This was the first conference on spumaretroviruses to be held in the Southern Hemisphere and in the unique environment of the rainforest. New developments and current perspectives in FV research were presented. Highlights of the conference included the structural biology of the envelope protein (Env) and insights into its function and evolution, epidemiologic identification of Amazonian indigenous people with a high prevalence of simian FV (SFV) infections, investigations of virus biology and genomics using synthetic FV DNAs, studies of humoral immune response, and development and applications of SFV vectors. The last day of the meeting was a special tour of the Centro de Primatologia do Rio de Janeiro, located northeast of Rio de Janeiro amidst the protected rainforest, where New World primate hosts of spumaretroviruses are rescued and studied. Our report summarizes the meeting highlights and outcomes for future discussions. Full article

Betula. platyphylla Sukaczev (B. platyphylla) forest is an important montane forest type. Global warming has impacted its distribution. However, how it affects suitable distribution across ecoregions and corresponding biodiversity protection measures remains unclear. This study used the Maxent model to analyze the suitable distribution and driving variables of B. platyphylla forest in China and its four ecoregions. The minimum cumulative resistance (MCR) model was applied to construct corridors nationwide. Results show that B. platyphylla forest in China is currently mainly distributed in the four ecoregions; specifically, in Gansu and Shaanxi Province in Northwest China, Heilongjiang Province in Northeast China, Sichuan Province in Southwest China, and Hebei Province and Inner Mongolia Autonomous Region in North China. Precipitation and temperature are the main factors affecting suitable distribution. With global warming, the suitable areas in China including the North, Northwest China ecoregions are projected to expand, while Northeast and Southwest China ecoregions will decline. Based on the suitable areas, we considered 45 corridors in China, spanning the four ecoregions. Our results help understand dynamic changes in the distribution of B. platyphylla forest in China under global warming, providing scientific guidance for montane forests’ sustainable development. Full article

The NW–SE-trending Firenze-Pistoia Basin (FPB) is an intermontane tectonic depression in the Northern Apennines (Italy) bounded to the northeast by a SW-dipping normal fault system. Although it has moderate historical seismicity (maximum estimated Mw 5.5 in 1895), the FPB lacks detailed characterization of its recent tectonic structures, unlike those of nearby basins that have produced Mw > 6 events. This study focuses on the southeastern sector of the basin, including the urban area of Florence, using tectonic geomorphology derived from remote sensing, in particular LiDAR data, field verification, and high-resolution geophysical surveys such as electrical resistivity tomography and seismic reflection profiles. The integration of these techniques enabled interpretation of the subdued and anthropogenically masked tectonic structures, allowing the identification of Holocene activity and significant, although limited, surface vertical offset for three NE–SW-striking normal faults, the Peretola, Scandicci, and Maiano faults. The Scandicci and Maiano faults appear to segment the southeasternmost strand of the master fault of the FPB, the Fiesole Fault, which now shows activity only along isolated segments and cannot be considered a continuous active fault. From empirical relationships, the Scandicci Fault, the most relevant among the three active faults, ~9 km long within the basin and with an approximate Late Quaternary slip rate of ~0.2 mm/year, might source Mw > 5.5 earthquakes. These findings highlight the need to reassess the local seismic hazard for more informed urban planning and for better preservation of the cultural and architectural heritage of Florence and the other artistic towns located in the FPB. Full article

Sepsis is a serious public health problem. sTREM-1 is a marker of inflammatory and infectious processes that has the potential to become a useful tool for predicting the evolution of sepsis. A prediction model for sepsis was constructed by combining sTREM-1, CRP, and a leukogram via a Bayesian network. A translational study carried out with 32 children with congenital heart disease who had undergone surgical correction at a public referral hospital in Northeast Brazil. In the postoperative period, the mean value of sTREM-1 was greater among patients diagnosed with sepsis than among those not diagnosed with sepsis (394.58 pg/mL versus 239.93 pg/mL, p < 0.001). Analysis of the ROC curve for sTREM-1 and sepsis revealed that the area under the curve was 0.761, with a 95% CI (0.587–0.935) and p = 0.013. With the Bayesian model, we found that a 100% probability of sepsis was related to postoperative blood concentrations of CRP above 71 mg/dL, a leukogram above 14,000 cells/μL, and sTREM-1 concentrations above the cutoff point (283.53 pg/mL). The proposed model using the Bayesian network approach with the combination of CRP, leukocyte count, and postoperative sTREM-1 showed promise for the diagnosis of sepsis. Full article